Problem Statement: Develop a machine learning model to accurately forecast weather conditions using historical data, providing users with reliable predictions for planning their activities.
Programming language: Python: Widely used for data preprocessing, model training, and deployment due to its extensive libraries for machine learning and data analysis (e.g., TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
Libraries:
● Model Deployment:
Flask or Django: Lightweight web frameworks in Python for building RESTful APIs to deploy machine learning models and serve predictions. Might as well use Docker, Kubernetes.
● Visualization and User Interface:
Plotly, Matplotlib, or Seaborn: Libraries for creating interactive visualizations and plots to analyze data and model predictions.
● Model Testing and Training:
Scikit-learn: For implementing machine learning algorithms and model evaluation.
● Model Evaluation Metrics:
Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), etc.
Presentation link: Canva Link
Demostration Video: Youtube Link
App Interface:
